Hierarchical Optimization of the Parallel FDTD Computations Based on the Macro Data Flow Graph Paradigm

A new algorithm for an optimized design of the FDTD (Finite Difference Time Domain) computations involved in simulations of electromagnetic wave propagation in irregular areas is presented in the paper. Computational programs are represented as macro data flow graphs (MDFG) which are to be partitioned and assigned to processors for optimal parallel execution. The proposed hierarchical optimization is based on two steps. The first step consists of a computation cell redeployment algorithm in irregular meshes where optimization is performed in three main phases: generation of an initial MDFG based on wave propagation area partitioning, MDFG nodes merging with load balancing to obtain given number of macro nodes and communication optimization to minimize and balance inter-node data transmissions. The second step is a connectivity-based distributed node clustering which creates an optimized MDFG. The hierarchical algorithm combines both methods to speedup parallel execution of the FDTD computations and to reduce the execution time of the optimization algorithm.